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Advanced Data Mining to Explore the Effects of brain Due to schizophrenia 2

Advanced Data Mining to Explore the Effects of Brain Due to ...

引用

2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： sangeetha, M. Deepika, s. Rajeshwari, G. Priyadharshini, b. souparnika, C.s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

The paper investigates changes in microstate dynamics across various schizophrenia stages. Changes in microstate dynamics across schizophrenia stages can be detected through K-means clustering of EEG data. Machine learning models for classifying different stages of schizophrenia include random forest, gradient boosting, and XGboost. Results show that there are significant changes in microstate dynamics during schizophrenia phases and this shows changes in brain processing. Furthermore, it can be noted from the use of machine learning models that their accuracy levels are quite impressive when it came to distinguishing different phases of schizophrenia through patterns generated by activities taking place inside our brains which are obtained from electroencephalography analysis. Evidently, such a statement reflects how a combination between machine learning capabilities with electroencephalography research has been used so far for this purpose which may imply a better understanding regarding its neurological underpinnings or else creation of early diagnostic devices before treatment commences. © 2024 IEEE.

关键词： Electroencephalography

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The Identification of Health of Heart Through Predictive ML based Technique in Integration with Existing system 2

The Identification of Health of Heart Through Predictive ML ...

引用

2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Prabakaran, s. Harish, s. Tamilselvan, b. Praveen Kumar, b. Gobinath, b. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

New classes of diseases include;cardiovascular diseases: These are diseases associated with the heart and blood vessels and they are some of the classes of emerging infectious diseases that threaten human health around the world. for public health, is a big blow to complicated the issue that this is becoming a problem gradually, many researchers have been developing complicated systems that integrate patient's electronic health records, as well as many others, and artificial neural networks algorithms in a bid to produce high diagnostic results. most of the frequent artificial intelligence particularly in a context where full patient data are instantiated for the purpose of inferring the heart diseases. and thereby merely claiming the most primordial facets of our population's health. describes with exemplary accuracy the use of four separate classification methods: The used models in the current study are a) Multilayer Perceptron (MLP) b) RandomForest (RF) c) support vector Machine (svM), and d) XGboost. before the development of the conceptual models, this study went through pre-processing and doing features extraction to these analyses These were done in line with what is regarded as the best approach when doing the last phase in a given research process. When evaluating the results, the following standards were used: accuracy, precision, recall, F1-score as it has been mentioned earlier, the XGboost model shows a very high level of effectiveness The accuracy rate is rather high, 88%, which means the effectiveness of the instrument is high. Thus, this research study will fill this research gap of knowledge, as mentioned earlier, in a way that is appreciable. is a clear step in the right direction in addressing the high error rate that is associated with cardiovascular diagnosis while at the same time enhancing the validity with the MLP as well as the svM. © 2024 IEEE.

关键词： support vector machines

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Decentralized Financing for Artistic Expression: A Crowdsourcing Model Powered by blockchain Technology 4

Decentralized Financing for Artistic Expression: A Crowdsour...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： saranya, R. sangavi, C. sarni, K.J. Dehavi, D. santhiyadevi, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

The blockchain with its decentralization, security, and transparency has disrupted the contemporary society. Another donor-based technique, crowdfunding, started as a way to fund projects with limited donations over the Internet and has also changed. Present scenario is that, currently people can put their money to work in startup ventures through brokers or digital wallets. Current crowdfunding sites have little control over where the money goes, and donors often do not have guarantees. In this paper, we present a potential solution as a blockchain and decentralized crowdfunding system. © 2024 IEEE.

关键词： Decentralized finance

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secure Online voting with Enhanced biometric verification Using Cryptography Approach 4

Secure Online Voting with Enhanced Biometric Verification Us...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Gunasekaran, s. Dhinesh, M. Ebinesh, M. Gowtham, b. Guruprasath, C.R. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

Electronic voting systems, increasingly used in modern elections, offer several enhancements over traditional methods, including better accuracy, convenience, flexibility, privacy, verifiability, and mobility. However, these systems are not without their shortcomings. They can be time-consuming to manage and still require significant amounts of paperwork. High-level officials often have no direct involvement in their operation. Additionally, the machines are prone to damage if not properly maintained, and their software typically does not support the simultaneous updating and editing of multiple items, which can hinder their efficiency. Here proposes a novel approach that integrates encrypted face recognition and score voting. The system leverages Haar Cascade Classification for face detection, extracting and encrypting facial features during user registration, and subsequently comparing encrypted features during the authentication process. The encrypted feature storage ensures user privacy and protects sensitive biometric information. Due to identification and authentication users are permitted to cast votes in the system using a score voting system that introduces more flexibility to the procedure. score voting or also called range voting is the type of voting where voters have the liberty to assign different scores to the given candidates or options. With reference to other methods of voting that enable the voters to vote for only one candidate, the score-based methods are much better at providing a gradation of the views of the voters. This feature allows for the verification of every process of the voting exercise. However, this ID is well hidden and even the system administrators cannot track this ID thus ensuring that no anyone can identify any of the voters. © 2024 IEEE.

关键词： Face recognition

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An AI-powered smart health companion that detects stress to aid medical support using artificial intelligence/machine learning 4

An AI-powered smart health companion that detects stress to ...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Gunasekaran, s. Kathirvel, s. Kavin, A. Logeshwaran, K. Patmesh, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

The name of the project is "An AI-powered smart health companion that detects stress to aid medical support using artificial intelligence/machine learning."It uses advanced technologies such as AI and ML, which has created a revolution in healthcare and changed people's approach to medical care. This initiative ensures personalized care and support by implementing innovative methods in medical aid coupled with stress detection through what can only be described as an elaborate blend of different technologies. Among the components used are React, ***, Python-based machine learning algorithms, MongoDb, and Firebase;they work together harmoniously to produce features like NLP chat application that allows users to easily engage in discussions about their health issues while receiving customized medical advice and suggestions. © 2024 IEEE.

关键词： Electronic health record

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IoT based speed Control and Accident Avoidance Using black box 2

IoT Based Speed Control and Accident Avoidance Using Black B...

引用

2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： suganya, R. sindhu, K. varshini, v. Nidharshana, b. siva Prabha, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

The system employs various sensors and advanced algorithms to lessen traffic hazards. Onboard sensors like GPs, accelerometers, gyroscopes, and proximity sensors track vehicle data in real-time. This data is analyzed locally or sent to a central unit for further processing. sophisticated computers assess the data to anticipate collision risks, predict dangers, and recommend safe speeds. Proactive measures, like automated speed adjustments and collision avoidance, are taken when hazards are detected. Communication technologies such as v2X facilitate real-time data sharing between infrastructure and vehicles, enhancing situational awareness and collaborative decision-making. A black box records crucial data for accident investigation and performance analysis. Machine learning algorithms continuously improve system functionality based on real-world data. Due to the usage of black box, the data which has been collected will sent to nearly located base station, police station, hospital, or home along with latitude and longitude of the vehicle's location. © 2024 IEEE.

关键词： Proximity sensors

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An Empirical analysis of Parkinson kind of problem via predictive Machine Learning technique 4

An Empirical analysis of Parkinson kind of problem Via predi...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： sangeetha, M. Ruchitha, v. subasni, K.M. vaishnavi, D. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350364729

Parkinson's disease (PD) is a growing neurodegenerative disorder that exhibits abnormal shifts and a sort of added dispassionate exhibitions. Achieving an exact diagnosis of PD can explain the expected intimidating task on account of the correspondence of signs and symptoms, specifically in the beginning stages, to those of alternative healing environments or the open declining process. The main focus of this study is to improve the PD demonstrative process through the exercise of a convolutional neural network, Random Forest, and support vector Machine - all forms of Machine Learning proposed at the distinctive middle from two points things outside PD and those with the ailment. This method centers on recognizing departures in subjects' changes using illustration responsibilities. Furthermore, this research investigates the approximate influence of two illustration tasks, namely the cable dies and the spiral five of something, in the bias process. Demonstrating veracity of 93.5%, our convolutional classifier, prepared on images from the five-of-something illustration task and engaging improving methods, can serve as an unprejudiced method for critical betwixt PD cases and athletic individuals. Our sleek model has the potential to develop into an offline evident-occasion robotic diagnostic finish for sole-task requests, surely implementable in a dispassionate environment. © 2024 IEEE.

关键词： Convolutional neural networks

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smart Airbag Wearables Revolutionizing Fall Protection with IoT Integration 2

Smart Airbag Wearables Revolutionizing Fall Protection with ...

引用

2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： balasubramani, M. Kavinkumar, s. Karthik, P. sekar, K.M. Gowtham, b. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368109

Internet of Things and smart airbag methodology together are enabling revolution in fall injury prevention. The device measures body temperature instantly and provides timely interfere. Temperature and other physiological parameters are monitored by embedded sensors and promptly analyzed using the IoT platform. When a fall is detected, the airbags are deployed quickly and the risk of injury is reduced, thanks to the fall detection feature. Alerts are quickly sent to individuals or emergency services via the IoT network. The partnership is set on enhancement of safety and delivery of value and quality within the partnership and is set on safety improvement;It also offers the highest guarantee of safety to people where previously they had been at risk of loss. © 2024 IEEE.

关键词： Physiological models

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Identifying Gestures through Convolutional Neural Networks: An Innovative Methodology 2

Identifying Gestures through Convolutional Neural Networks: ...

引用

2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Anbumani, P. Arun, L. Arunkumar, v. Anish, v. Gokula Hariharan, N. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368109

Recognizing hand gestures holds significant importance in computer vision, influencing fields such as sign language interpretation, gaming, and human-computer interaction. While Convolutional Neural Networks (CNNs) have become a prominent solution for various computer vision tasks, including hand gesture recognition, our research diverges by proposing an alternative method. We introduce a novel approach to hand gesture recognition that employs a CNN architecture. Initial preprocessing enhances hand photo quality by refining borders and eliminating background noise. Following this, our CNN architecture, which includes multiple convolutional and fully connected layers, extracts unique features from hand images. Training on a substantial dataset and evaluating on a separate test set, our method surpasses alternative techniques in accuracy for hand gesture recognition. These results underscore the effectiveness of our approach and suggest its practical utility. Hand gestures, as a prevalent form of communication in modern society, hold significant potential for creating intuitive user interfaces across diverse applications. While previous approaches often struggled with reliable gesture classification across individuals, our proposed method, utilizing four CNNs, achieves real-time recognition of hand gestures. Achieving an average accuracy of 98.76% on a dataset covering nine hand motions, our CNN-based approach demonstrates promising results for real-world applications. © 2024 IEEE.

关键词： Convolutional neural networks

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Hue spectrum visualizer using python with OpenCv 2

Hue Spectrum visualizer using python with OpenCV

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2nd IEEE International Conference on IoT, Communication and Automation Technology, ICICAT 2024

作者： Raajyavardhini, A. Gowthaman, T. Krishnamoorthy, R. Dhanush, s. Harish, s. V.S.B. Engineering College Department of Computer Science and Engineering Karur India

ISBN: (纸本)9798350368109

Color analysis is a significant source in many image processing processes consisting of automotive vehicle navigation, protest detection, traffic sign recognition, skin color analysis, and object tracking. The approach adopted in this study mainly relies on the ability to locate the color name right at the center of the camera frame and determine the objects of red, green, and blue colors using the bounding box property. by rating the amount of red, green and blue of each pixel's outfits, the colors of these pixel are revealed. Next, all objects of interest that fall within the video segment of interest are detected and located using rectangular boundary boxes based on the Hsv color model. The process used in this process entails the use of a dataset that has a tabular form with data on color names and its values to arrive at the best match. The values of Red, blue, and Green (RGb) as well as color names of each pixel are extracted, providing the means to track the three separate colors in the video stream. When a color is not detected in the reference data but observed in the real-time stream, a box surrounds the mentioned color: the color name is written above the box. It enhances the approaches to recognition of color and also provides significant improvements in the field of robotics. The application of these techniques generally involves the use of the OPENCv software library together with the PYTHON programming language. © 2024 IEEE.

关键词： Python

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